发布求助
文献互助 智能选刊 最新文献

2010 Annual Meeting of the North American Fuzzy Information Processing Society最新文献

筛选
英文 中文
A new method of Multi Dimensional Scaling 一种新的多维标度方法
2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548299
G. Massini, Stefano Terzi, M. Buscema
{"title":"A new method of Multi Dimensional Scaling","authors":"G. Massini, Stefano Terzi, M. Buscema","doi":"10.1109/NAFIPS.2010.5548299","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548299","url":null,"abstract":"This paper presents a new algorithm called “Population” that is an efficient and high speed method of performing Multi Dimensional Scaling based only on the calculation of a local fitness. Population is not bound to a specific Cost Function but is possible to define its in relation to the considered objective. The motivation for its creation was for use in the elaboration of datasets of great dimensions. In performance comparisons between Population and the Sammon method, Population has consistently excelled. Because of the nature of the algorithm, it is not necessary for the data set to be complete at the moment of the elaboration, for new data can be introduced dynamically in the system.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125953609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
How to relate fuzzy and OWA estimates 如何关联模糊和OWA估计
2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548275
T. Magoc, V. Kreinovich
{"title":"How to relate fuzzy and OWA estimates","authors":"T. Magoc, V. Kreinovich","doi":"10.1109/NAFIPS.2010.5548275","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548275","url":null,"abstract":"In many practical situations, we have several estimates x<inf>1</inf>, …, x<inf>n</inf> of the same quantity x, i.e., estimates for which x<inf>1</inf> ≈ x, x<inf>2</inf> ≈ x, …, and x<inf>n</inf> ≈ x. It is desirable to combine (fuse) these estimates into a single estimate for x. From the fuzzy viewpoint, a natural way to combine these estimates is: (1) to describe, for each x and for each i, the degree μ≈(x<inf>i</inf>-x) to which x is close to x<inf>i</inf>, (2) to use a t-norm (“and”-operation) to combine these degrees into a degree to which x is consistent with all n estimates, and then (3) find the estimate x for which this degree is the largest. Alternatively, we can use computationally simpler OWA (Ordered Weighted Average) to combine the estimates x<inf>i</inf>. To get better fusion, we must appropriately select the membership function μ≈(x), the t-norm (in the fuzzy case) and the weights (in the OWA case). Since both approaches - when applied properly - lead to reasonable data fusion, it is desirable to be able to relate the corresponding selections. For example, once we have found the appropriate μ≈(x) and t-norm, we should be able to deduce the appropriate weights - and vice versa. In this paper, we describe such a relation. It is worth mentioning that while from the application viewpoint, both fuzzy and OWA estimates are not statistical, our mathematical justification of the relation between them uses results that have been previously applied to mathematical statistics.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"329 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124645264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Classification using an adaptive fuzzy network 采用自适应模糊网络进行分类
2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548179
N. Pizzi, A. Demko, W. Pedrycz
{"title":"Classification using an adaptive fuzzy network","authors":"N. Pizzi, A. Demko, W. Pedrycz","doi":"10.1109/NAFIPS.2010.5548179","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548179","url":null,"abstract":"The analysis of feature variance is a common approach used for data interpretation. In the case of pattern classification, however, the transformation of correlated features into a new set of uncorrelated variables must be used with caution, as there is no necessary causal connection between discriminatory power and variance. To compensate for this potential shortcoming, we present a classification method that blends variance analysis with an adaptive fuzzy logic network that identifies the most discriminatory set of uncorrelated variables. We empirically evaluate the effectiveness of this method using a suite of biomedical datasets and comparing its performance against two benchmark classifiers.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125472756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Measurement theory and subsethood 测量理论与亚群体
2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548269
M. J. Wierman, W. J. Tastle
{"title":"Measurement theory and subsethood","authors":"M. J. Wierman, W. J. Tastle","doi":"10.1109/NAFIPS.2010.5548269","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548269","url":null,"abstract":"The connection between logical implication and the subsethood relationship is apparent when bivalent logic and crisp set theory are examined. When fuzzy logic and fuzzy set theory are examined, however the connection is not always clear. Ragin Ragin (1987) introduced fuzzy subsethood into the social sciences as a tool for detecting necessary and sufficient conditions. Unfortunately, Ragin's efforts were dismissed by social scientists becasue of the problem of scale. This paper examines the use of fuzzy subsethood as tools for detecting causality.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125543199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Applying nonlinear learning scheme on AntNet routing algorithm 非线性学习方案在蚁网路由算法中的应用
2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548215
Pooia Lalbakhsh, Bahram Zaeri, M. Fesharaki
{"title":"Applying nonlinear learning scheme on AntNet routing algorithm","authors":"Pooia Lalbakhsh, Bahram Zaeri, M. Fesharaki","doi":"10.1109/NAFIPS.2010.5548215","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548215","url":null,"abstract":"The paper deals with a conceptual modification on the learning phase of AntNet routing algorithm through nonlinear reinforcement. Since the learning structure of AntNet consists of colonies of learning automata, the proposed approach replaces the previously defined linear learning automata structure with nonlinear learning automata, which modifies the reinforcement process without imposing overhead into the system. In order to select the appropriate nonlinear functions, the convergence rates are mathematically analyzed and the functions with better rates are replaced at the core of the system's learning cycle. To have an appropriate comparison four non-linear AntNet algorithms are considered and simulated on NSFNET topology, which are compared with the standard AntNet. Simulation results show that the vital performance metrics (e.g. packet delay, throughput, and network awareness) are improved using some forms of nonlinear learning functions.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129522847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Recommendations in Twitter using conceptual fuzzy sets Twitter中使用概念模糊集的推荐
2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548208
Takatoshi Sakaguchi, Yuya Akaho, T. Takagi, Takuya Shintani
{"title":"Recommendations in Twitter using conceptual fuzzy sets","authors":"Takatoshi Sakaguchi, Yuya Akaho, T. Takagi, Takuya Shintani","doi":"10.1109/NAFIPS.2010.5548208","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548208","url":null,"abstract":"Recently, though there are a lot of techniques to rank information there are few studies on how to rank users and thus help to form online communities. We propose the use of a system to recommend the user by analyzing his or her interests, and using Conceptual Fuzzy Sets to expand a query. We show the effectiveness of using Conceptual Fuzzy Sets for recommending users. This can be applied to forming communities.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122057931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 12
A hybrid approach for multi-criteria decision problems 多准则决策问题的混合方法
2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548201
Karima Sedki, V. Delcroix
{"title":"A hybrid approach for multi-criteria decision problems","authors":"Karima Sedki, V. Delcroix","doi":"10.1109/NAFIPS.2010.5548201","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548201","url":null,"abstract":"There are several situations where humans express their preferences in order to take good decisions. The major problem is that humans' preferences are more and more complex, the multiple criteria considered are often conflicting and the number of alternatives is too large to be explicitly handled. The objective of Multi-Criteria Decision Making (MCDM) approaches is to efficiently model and solve such complex decision problems. In this paper, we propose a framework allowing on one hand to encode users' preferences about the alternatives regarding the available criteria using a logic-based approach which is a variant of the Qualitative Choice Logic (QCL). On the other hand, the importance of each criterion is considered and computed in terms of probability degrees with respect to what is already known about the person who takes the decision. The available alternatives are then evaluated following two aspects: the first one concerns verifying if a given alternative is satisfied in the preferred models of the users' preferences while the second one is related to the criterion's importance.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116833797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Acoustic emission signal feature analysis using type-2 fuzzy logic System 基于二类模糊逻辑系统的声发射信号特征分析
2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548197
Qun Ren, L. Baron, M. Balazinski, K. Jemielniak
{"title":"Acoustic emission signal feature analysis using type-2 fuzzy logic System","authors":"Qun Ren, L. Baron, M. Balazinski, K. Jemielniak","doi":"10.1109/NAFIPS.2010.5548197","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548197","url":null,"abstract":"In this paper, type-2 fuzzy logic system is applied to analyse acoustic emission signal feature for tool condition monitoring in a tool micromilling process. To make the comparison and evaluation of AE signal features easier and more transparent, Type-2 fuzzy analysis is used as not only a powerful tool to model AE SFs, but also a great estimator for the ambiguities and uncertainties associated with them. Depend on the estimation of root-mean-square error (RMSE) and variations in modeling results of all signal features, reliable ones are selected and integrated into tool wear evaluation. A discussion and comparison of results is given.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128361242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 11
Interval type-2 Boolean fuzzy systems are universal approximators 区间型-2布尔模糊系统是普遍逼近器
2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548180
F. You, H. Ying
{"title":"Interval type-2 Boolean fuzzy systems are universal approximators","authors":"F. You, H. Ying","doi":"10.1109/NAFIPS.2010.5548180","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548180","url":null,"abstract":"Unlike the Mamdani and TS fuzzy systems, a Boolean fuzzy system, type-1 or type-2, employs a fuzzy implication to interpret its rules. There exist three families of type-2 fuzzy implications – R-implication, S-implication and QL-implication. In this paper, using the same technique that we developed previously [22, 23], we constructively prove that all the interval type-2 Boolean fuzzy systems, regardless of the implication they use, are universal approximators in that they are capable of uniformly approximating any real multivariate continuous function on a compact domain to any degree of accuracy.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121088603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Design and implementation of a Mamdani Fuzzy Inference System on an FPGA using VHDL 基于VHDL的Mamdani模糊推理系统的FPGA设计与实现
2010 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2010-07-12 DOI: 10.1109/NAFIPS.2010.5548190
Davi Nunes Oliveira, Gustavo Alves de Lima Henn, Otacílio da Mota Almeida
{"title":"Design and implementation of a Mamdani Fuzzy Inference System on an FPGA using VHDL","authors":"Davi Nunes Oliveira, Gustavo Alves de Lima Henn, Otacílio da Mota Almeida","doi":"10.1109/NAFIPS.2010.5548190","DOIUrl":"https://doi.org/10.1109/NAFIPS.2010.5548190","url":null,"abstract":"The growth of fuzzy logic applications led to the need of finding efficient ways to implement them. The FPGAs (Field Programmable Gate Arrays) are reconfigurable logic devices that provide mainly practicality and portability, with low consumption of energy, high speedy of operation and large capacity of data storage. These characteristics, combined with the ability of synthesizing circuits, make FPGAs powerful tools for project development and prototyping of digital controllers. In this paper, the implementation of a Mamdani Fuzzy Inference System has been demonstrated using VHDL programming language. The accuracy of the model on FPGA was compared with simulation results obtained using MATLAB & Fuzzy Logic Tool Box.","PeriodicalId":394892,"journal":{"name":"2010 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121760652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 10
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信